isprs annals III 3 333 2016
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![Figure 5: Plane in canonical form Evector = [0, 0, 1, 0]T with normal N = [0, 0, 1]T. The confidence region is a hyperboloid oftwo sheets, specified by the covariance matrix (7).](https://thumb-ap.123doks.com/thumbv2/123dok/3218837.1394993/4.595.56.289.89.210/figure-plane-canonical-evector-condence-hyperboloid-specied-covariance.webp)
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Characteristics of the Nepal earthquake and its main after shocks (reported by http://earthquake.usgs.gov/).. The main detected anomalies for Nepal earthquake using the
KEY WORDS: Deformation analysis, material testing, load test, close range photogrammetry, multi camera, image
However, we are looking for a solution to maximize the benefits from the concepts of intrinsic curves in order to first, reduce the disparity search space without
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This paper introduces a new image-guided non-local dense matching algorithm that focuses on how to solve the following problems: 1) mitigating the influence of vertical parallax
Considering the rotation and scale change between the transformed local regions, the difference of Gaussians (DoG) detector is adopted to extract the point
We have shown that camera calibration with distortion parameters can be incorporated to structureless bundle adjustment and results with precision in object space
The basic concept behind this is the detection, extrac- tion, localisation and matching of high-level features present in the aerial imagery (road network and its components, areas
